Original Research—General Otolaryngology
The Cost and Inpatient Burden of Treating Mandible Fractures: A Nationwide Inpatient Sample Database Analysis
Otolaryngology– Head and Neck Surgery 2014, Vol. 151(4) 591–598 Ó American Academy of Otolaryngology—Head and Neck Surgery Foundation 2014 Reprints and permission: sagepub.com/journalsPermissions.nav DOI: 10.1177/0194599814542590 http://otojournal.org
Israel Pena Jr, MD1, Laura Evelyn Roberts1, W. Marshall Guy, MD1, and Jose P. Zevallos, MD1
No sponsorships or competing interests have been disclosed for this article.
Abstract Objective. To discuss patient demographics, hospitalization characteristics, and costs associated with the treatment of mandible fractures.
reconstruction, open reduction internal fixation, length of stay, hospital cost Received February 1, 2014; revised April 11, 2014; accepted June 17, 2014.
Introduction
Study Design. Cross-sectional study. Setting. The 2009 Nationwide Inpatient Sample (NIS) database. Subjects/Methods. Patient demographics, hospital characteristics, fracture locations, and common comorbidities for patients with isolated mandible fractures were analyzed, and variables associated with increased cost and length of hospitalization stay were ascertained. Results. A total of 1481 patients were identified with isolated mandible fractures. The average age was 32, 85.4% were male, 39% were Caucasian, and 25% African American. Forty percent were from the lowest median household income quartile, and 77% were uninsured or government funded. The average length of stay (LOS) was 2.65 days, and average hospitalization cost was $35,804. A statistically significant increased LOS was associated with alcohol abuse, drug abuse, mental illness, diabetes mellitus type 2, cardiovascular disease, HIV, and age over 40. There was a statistically significant increased total cost associated with drug abuse, alcohol abuse, mental illness, cardiovascular disease, and age over 40. Conclusion. The average cost for treatment of mandible fractures was $35,804 per person with increased expenditures for older patients and those with a history of mental illness, cardiovascular disease, or substance abuse. To improve outcomes and reduce hospital charges, outpatient resources and inpatient protocols should be implemented to address the factors we identified as contributing to higher costs and increased hospital stay. Keywords isolated mandible fracture, facial fractures, jaw fracture, national inpatient sample database, facial plastic and
National Healthcare Expenditures Accounts data from 2011 show that the United States spends $2.7 trillion per year on health care, $8,680 per person, and is projected to continue to increase.1 In an effort to make health care delivery more efficient while maintaining high-quality care, it is important to investigate factors contributing to this nationwide problem. Nahlliah et al2 investigated patient characteristics and hospitalization charges associated with the management of all facial fractures on a national level using the 2008 Nationwide Inpatient Sample (NIS) database and found that facial fracture reduction in the United States contributed to an inpatient hospital cost of $1.06 billion. Mandible fractures are the most common facial fractures requiring reduction and account for more than half of all hospitalization charges and length of stay (LOS).2 Mandible fractures occur most commonly in adult males2-6 with a disproportionally high percentage (19.8%) of African Americans.2 Mandible fractures are most commonly due to assault, followed by motor vehicle accidents and accidental falls,2-4,7-11 with alcohol and drug abuse commonly reported comorbidities.2,12,13 Previous studies have evaluated the cost of treating mandible fractures among different settings. Outpatient 1 The Bobby R. Alford Department of Otolaryngology–Head and Neck Surgery, Baylor College of Medicine, Houston, Texas, USA
This article was presented as a poster at the 2013 AAO-HNSF Annual Meeting & OTO EXPO; September 29–October 3, 2013; Vancouver, British Columbia, Canada. Corresponding Author: Israel Pena Jr, MD, The Bobby R. Alford Department of Otolaryngology– Head and Neck Surgery, Baylor College of Medicine, One Baylor Plaza, NA102, Houston, Texas 77030, USA. Email: [email protected]
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repair of mandible fractures was shown to be more costefficient compared to repair after direct hospitalization,14,15 but a delay in treatment, after 72 hours, is also associated with an increase in infection rates for both closed reduction (CR) and open reduction and internal fixation (ORIF).16-19 According to Maloney et al,18 patients treated within 72 hours of presentation had a 0.6% infection rate compared to the average infection rate of 4.4% for mandible repairs. Despite this finding, Dillion et al2 showed that hospital admission resulted in a mean bill $5876 higher than that of patients who were not admitted, especially if transferred from an outside facility as opposed to being admitted from the emergency department. Mandible fractures are most commonly managed by ORIF due to more predictable healing and more precise reduction when significant displacement, malocclusion, or other midface fractures are present.20,21 ORIF is also associated with better functional results, decreased pain,22 quicker return to school or work,23 and decreased masticatory disability resulting from prolonged immobilization.24 Although ORIF is associated with initial increased cost2,7,20,25-29 and increased LOS7,25,27,28 compared to CR, the benefits of ORIF are of particular importance in the large population of noncompliant patients in which there is a greater risk for postoperative complications and a higher potential for long-term cost.27 Dodson et al26 found that postoperative infection contributed to an average additional cost of $11,637 per patient. To date, there have been no studies that have evaluated variables associated with discrepancies in cost and LOS in the treatment of mandible fractures on a national level. The purpose of this cross-sectional analysis was to identify the patient demographics and hospital characteristics associated with the treatment of mandible fractures and to correlate these factors with cost and LOS using a national hospital database. By identifying populations most at risk and comorbidities associated with higher costs, we hope to elucidate preventive interventions targeting these different groups and subsequently help to ameliorate the financial burden of mandible fractures on the health care system.
Materials and Methods Study Design/Sample
intubation, and patients with concurrent neurological injury including altered mental status, comatose, and intracranial bleed. The intention was to exclude those patients with complex injuries whose hospital course was not solely related to the treatment of their mandible fracture.
Variables The first variables examined were age, gender, race, income level, and insurance type. These characteristics were decided on to better understand the demographics of the patients requiring treatment for a mandible fracture. Age was further broken down into 2 brackets, age .40 and age \40, and average cost and LOS was determined for each bracket to extrapolate if a certain age group incurs greater costs. Income level was also further subdivided into categories including less than $39,000, $39,000 to 48,000, $48,000 to 63,000, and greater than $63,000. These variables were analyzed to determine the most common gender, race, average age, and income bracket level associated with mandible fractures as well as the average cost and LOS for each. Similarly, payment type was divided into Medicare, Medicaid, HMO/private, self-pay, other, and no charge. These data were analyzed to determine average cost and LOS depending on payer type. Other variables analyzed included hospital characteristics: bed size of hospital stratified into large hospitals (.100 beds), medium size hospitals (50-99 beds), and small hospitals (\ 50 beds); hospital location (urban vs rural); hospital region; and academic versus nonacademic hospital. These hospital characteristics were further analyzed to determine average cost and LOS. The comorbidities substance abuse, mental disorders, alcohol abuse, diabetes mellitus type 2 (DM2), cardiovascular (CV) disease, hepatitis C, and human immunodeficiency virus (HIV) were assessed in diagnosis fields 1 through 10 using ICD-9 codes. The average LOS and cost for cases with these prominent comorbidities were then determined and compared to overall average hospital LOS and cost. Information pertaining to location and number of fractures, type of surgical procedure (ORIF or CR), day hospitalization procedure was performed, and postoperative complications were also analyzed in terms of cost and LOS.
Data Analyses
A cross-sectional analysis was conducted by analyzing the 2009 Nationwide Inpatient Sample database for patients with isolated mandible fractures. Since it is a secondary data set made available through the AHRQ, Institutional Review Board approval was not required. The NIS data set provides hospital characteristics and information on nearly 100 patient- and hospital-related variables. Patients included in this study had an ICD-9 code (International Classification of Diseases, 9th Revision, Clinical Modification) for mandible fracture (802.20 through 802.37) listed as the primary admitting diagnosis. Exclusion criteria included patients with poly-trauma, defined as any additional fracture occurring outside the mandible, patients with severe respiratory distress requiring
Average cost and LOS were calculated from the information provided in the data set for each of the variables analyzed. These values were then compared using 2-tailed t tests, and a P value was calculated to determine statistical significance of the means. When more than 2 variables were compared, P values were based on all pairwise multiple comparison procedures (Dunn’s Method). A P value of \.05 was considered significant. All statistical analyses were performed using SigmaPlot v.12.5 (Systat, Inc, Chicago, Illinois) statistical software.
Results A total of 1481 patients with isolated mandible fractures were identified. Average age was 32 years, and the vast
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Table 1. Patient Demographic Statistics (N = 1481). Study Variable Age (yrs) \40 40 Gender Male Female Unknown Race White Black Hispanic Native American Asian Other Income \$39,000 $39,000-49,000 $48,000-63,000 .$63,000 Insurance type Medicare Medicaid Private Self-pay Other No charge
Table 2. Patient Comorbidities Statistics. Data (%) 32 1101 (74.3) 380 (25.7) 1265 (85.4) 204 (13.8) 12 (0.8) 573 367 176 7 13 108
(38.7) (24.8) (11.9) (0.5) (0.9) (7.3)
542 362 260 180
(40.3) (26.9) (19.3) (13.4)
91 362 334 454 192 48
(6.1) (24.4) (22.6) (30.7) (13) (3.2)
Study Variable Psychiatric disorder Present Not present Alcohol abuse Present Not present Drug abuse Present Not present DM 2 Present Not present CV disease Present Not present HIV Present Not present Hepatitis C Present Not present
Data (%)
81 (5.5) 1400 (94.5) 174 (11.7) 1307 (88.3) 95 (6.4) 1386 (93.6) 35 (2.4) 1446 (97.6) 160 (10.8) 1321 (89.2) 21 (1.4) 1460 (98.6) 27 (1.8) 1454 (98.2)
Abbreviations: DM2, diabetes mellitus type 2; CV, cardiovascular disease; HIV, human immunodeficiency virus.
Table 3. Hospital Demographic Statistics. Study Variable
majority of patients were male (85.4%). Thirty-nine percent of patients were Caucasian, 25% African American, 12% Hispanic, 7% other, and 1% Asian (Table 1). Twelve percent of patients had a history of alcohol abuse at presentation, and 10.7% had a history of illicit drug abuse. A history of mental illness was found in 5.5% of patients. Two percent of patients were diabetic, 1.4% had HIV, 1.8% had hepatitis C, and 10.8% had comorbid cardiovascular (CV) disease (Table 2). Forty percent of patients were from the lowest median household income quartile (earning less than $39,000), 27% from the second quartile ($39,000-$48,000), 19% third quartile ($48,000-$63,000), and 13% in the top household income quartile (.$63,000). Seventy-seven percent of patients were either uninsured or government funded (Table 1). Eighty-two percent of patients were treated in academic and 18% in nonacademic hospitals. Seventy-two percent of patients were treated at large hospitals (.100 beds), 24% in medium size hospitals (50-99 beds), and 4% in small hospitals (\50 beds). The majority of patients (95%) were treated in an urban hospital setting, and 66% were treated in the South or Northeast (Table 3). A minority of patients had a single fracture (41%). Angle fractures were the most common (42%), followed by symphysis (39%), body (34%),
Affiliation Academic Nonacademic Size Small Medium Large Location Rural Urban Region Northeast Midwest South West
Data (%)
1211 (82) 270 (18) 61 (4) 335 (23) 1037 (72) 80 (5) 1401 (95) 437 267 537 240
(30) (18) (36) (16)
condyle (24%), and ramus (9%). There was no statistical difference between location of fracture and cost or LOS. Ninety-six percent of patients underwent ORIF, 2% underwent CR, and the remaining 2% underwent surgical procedure not otherwise specified (NOS) with no associated increase in LOS or cost. Thirty-eight percent of patients
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underwent surgical intervention within 24 hours of admission, 83% underwent intervention within 72 hours, and there was a 0.5% complication rate, which included postoperative infection and hematoma, with no associated increase in LOS or cost. Mean LOS was 2.96 days for the entire cohort, and the average cost of hospitalization was $35,804 (Table 4). LOS was noted to be significantly higher in patients with a history of alcohol abuse (3.8 vs 2.85 days, P \ .001), drug abuse (4.68 vs 2.84 days, P \ .001), mental illness (3.98 vs 2.90 days, P = .005), DM2 (4.23 vs 2.93 days, P = .008), CV disease (3.93 vs 2.84, P \ .001), HIV (4.71 vs 2.93, P \ .001), and age over 40 (3.68 vs 2.71 days, P \ .001) (Tables 4, 5). Patients treated in academic institutions had a shorter LOS compared to those treated in nonacademic institutions (2.91 vs 3.17 days, P = .03), however this was not clinically significant (Table 6). No significant difference in average LOS was noted with income quartile, gender, race, comorbid hepatitis C, hospital region or size, or rural versus urban setting (Tables 4, 6). Total cost was significantly higher in patients with a history of drug abuse ($56,251 vs $34,399, P \ .001), alcohol abuse ($44,007 vs $34,656, P \ .001), psychiatric disorders ($37,422 vs $35,713, P = .047), as well as in patients older than 40 ($38,769 vs $34,782, P = .013) and in patients with CV disease ($43,554 vs $34,870, P \ .05). Though the Asian population had a high average cost ($47,692) and LOS (6.38 days), this was skewed by 1 outlier with a cost of $134,000 and LOS of 33 days due to anoxic brain injury and grand mal seizures. Regardless, this was not statistically significant. There was also no significant difference in total cost in terms of academic versus nonacademic hospitals, rural versus urban setting, race, gender, diabetes, HIV or hepatitis C status, income quartile, or insurance status (Tables 4-6).
Discussion The NIS database provides a 20% stratified sample of US hospital admissions, making it an ideal database to study isolated mandible fractures. In an effort to decrease the nationwide financial burden, our aim was to identify variables associated with increased cost of hospitalization and LOS for the treatment of isolated mandible fractures. With a sample population of 1481 patients that met our inclusion and exclusion criteria, our results confirm that isolated mandible fractures incur a significant financial burden with an average hospitalization cost per patient of $35,804. As supported by previous studies,2,7 we found that the majority of patients affected by isolated mandible fractures requiring treatment are uninsured (47%) males of lower socioeconomic status with a disproportionately high percentage of African Americans. Thirty-nine percent of the sample population was Caucasian and 25% African American (Table 1), which differs markedly from the national population of 77.9% Caucasians and 13.1% African Americans.30 Of the various patient demographics we studied, only age older than 40 was associated with a statistically significant increase in cost and LOS (Table 4).
In terms of hospital characteristics, our study found that smaller hospitals were associated with a significantly lower cost than medium and large hospitals, with no difference in the LOS between the 3. This may be related to the higher charges seen in larger cosmopolitan areas as well as academic institutions where larger hospitals are more likely to be located compared to rural settings. Interestingly, the only significant difference in terms of hospital location was the higher average charges seen in the Northeast versus the Midwest region even though the average LOS remained same in both areas. In order to reign in the excess costs in the Northeast, further studies would be needed to determine the etiology of the increased costs, which may be a reflection of higher costs of living, regional differences in malpractice risks and claims, or may reflect differences in inpatient care that could potentially be avoided. In comparing academic versus nonacademic institutions, academic institutions had an increased cost of hospitalization (P = .649) but a slightly more rapid patient turnover that was statistically significant yet clinically irrelevant (2.91 vs 3.17, P = .031) (Table 6). Many studies have reported similar findings with academic institutions accruing higher costs than nonacademic, which was partly attributed to the higher degree of severity of patients treated at academic institutions.31,32 In addition, Ayanian et al33 determined that academic hospitals had surgical times on average 36 minutes longer than nonacademic hospitals, thus acquiring higher surgical costs. Comorbidities were also analyzed (Tables 3, 5). Previous studies agree that alcohol and drug users have an increased incidence of facial fractures.2,7 While the national average of illicit alcohol/drug abuse is 9.1%, we reported an incidence of 12% alcohol abuse and 11% drug abuse.34 Alcoholics stayed approximately 1 day longer (P \ .001) and were billed almost $10,000 more compared to nonalcoholics (P \ .001). Numerous variables, including cost of treating intoxication/withdrawal states, prolonged wound healing with increased risk of infection, and unreliable compliance to follow-up may help to explain these data. Similar to the data on alcohol abuse, those with concurrent drug use stayed almost 2 days longer (P \ .001) and had an average cost of about $22,000 more (P \ .001). It is therefore essential to proactively recognize these patient populations quickly to address their disposition and postoperative care in order to minimize prolonged hospitalizations. In addition, implementing population-wide screening and intervention programs for substance abuse may potentially decrease the cost and LOS in these patients who present with isolated mandible fractures. Mental illnesses had a prevalence of 5.5%, notably higher than the overall national prevalence of 4.1%.35 Patients with psychiatric disorders stayed in the hospital 1 day longer (P = .005) with a hospital cost of almost $2000 more (P \ .047). CV disease was prevalent in 10.8% of patients (consistent with the national prevalence for our sample’s average age) and was associated with a hospitalization of over 1 day longer (P \ .001) and $9000 more
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Table 4. Mean Cost and LOS for Patient Demographic Variables. Study Variable Patient sample Age \40 40 Gender Male Female Race White Black Hispanic Native American Asian Income \$39,000 $39,000-48,000 $48,000-63,000 .$63,000 Insurance Medicare Medicaid Private Self-pay No charge
Mean Cost
P Value
Mean LOS
P Value
$35,804 — $34,782 $38,769 — $36,003 $34,760 — $34,576 $36,990 $38,248 $37,323 $47,692 — $33,864 $36,169 $35,314 $37,443 — $40,165 $37,601 $36,241 $36,414 $26,922
— .013*
2.65 — 2.71 3.68 — 2.96 2.96 — 2.97 2.58 2.99 3 6.38 — 2.8 3.09 2.89 3.38 — 3.41 2.82 3.12 2.87 2.27
— \.001
.479
.314
.368
.096
.618
.102
.312
.131
Abbreviations: LOS, length of stay. *Statistical significance.
(P \ .05) than those without CV disease.36 In addition, the grossly underreported prevalence of HIV in our patient population was 1.4%, markedly higher than the national prevalence, 0.38%, which includes both those diagnosed and those infected but undiagnosed.34 Clinicians should consider HIV screening in patients with isolated mandible fractures given the greater than threefold increased likelihood of having HIV in these patients compared to the general population due to the high morbidity and mortality associated with untreated HIV. Of note, patients with HIV or DM2 were hospitalized 1 day longer but accrued no significant difference in cost. It is unclear, however, from the NIS database whether the increased cost or LOS associated with these comorbidities was due to the management of these diseases or the disease impact on the treatment of mandible fractures. Therefore, further studies are indicated to differentiate these factors in order to understand how to eliminate the higher costs and/or LOS in these population subtypes. One of the major limitations of this study is the inability to analyze the itemized billing costs, but rather only the average cost of hospitalization per patient. We are therefore unable to establish a direct causal relationship between the variables assessed and the cost and LOS. The associations highlighted, though, can help to elucidate factors to be
aware of when treating patients with mandible fractures. Also, from the information provided by the NIS database, mode of injury could not be ascertained. Motor vehicle accidents and sports-related injuries are more likely to result in poly-trauma, and assault is most likely to result in an isolated mandible trauma.37,38 By intentionally excluding poly-trauma to analyze costs associated specifically with mandible fractures, our study was skewed to include a higher proportions of assault-associated injuries. Another weakness encountered is that the NIS database grossly underestimates the complication rates (0.5%) of treating isolated mandible fractures compared to other studies (5.3%) because it relies on ICD-9 diagnosis codes.39 It was unclear whether diagnoses such as malocclusion, nonunion, nerve injury, and broken tooth were secondary to the initial insult or were surgical complications, and they were therefore excluded as complications. There is much discrepancy in the literature regarding the most common mandible fracture location. The body, angle, and condyle are the top 3 most commonly cited locations.25,40,41 Our study found angle, symphysis, and body to be the most common locations. The underrepresentation of condylar fractures and exclusion of children in our study may be responsible for the low number of CR procedures (2%).42 The higher percentage of angle fractures in our
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Table 5. Mean Cost and LOS for Patient Comorbidities Variables. Study Variable Psychiatric disorder Present Not present Alcohol abuse Present Not present Drug abuse Present Not present DM2 Present Not present CV disease Present Not present HIV Present Not present Hepatitis C Present Not present
Mean Cost
$37,422 $35,713 — $44,007 $34,656 — $56,251 $34,399 — $39,697 $35,711 — $43,554 $34,870 — $36,388 $35,797 — $42,028 $35,690
P Value
Mean LOS
\.047*
— 3.98 2.90 — 3.80 2.85 — 4.68 2.84 — 4.23 2.93 — 3.93 2.84 — 4.71 2.93 — 3.52 2.95
\.001*
\.001*
.106
\.050*
.317
.283
P Value .005*
\.001*
\.001*
.008*
\.001*
\.001*
.367
Abbreviations: LOS, length of stay; DM2, diabetes mellitus type 2; CV, cardiovascular disease; HIV, human immunodeficiency virus. *Statistical significance.
Table 6. Mean Cost and LOS for Hospital Characteristics.a Study Variable Affiliation Academic Nonacademic Size Small Medium Large Location Rural Urban Region Northeast Midwest South West
Mean Cost
P Value
Mean LOS
P Value
— $36,185 $34,087 — $26,225 $34,914 $36,996 — $29,257 $36,181 — $40,238 $30,242 $34,523 $36,786
.649
— 2.91 3.17 — 2.43 2.82 3.04 — 2.78 2.97 — 2.94 2.94 2.92 3.10
.031*
.005*
.22
.005*
.602
.542
.963
Abbreviation: LOS, length of stay. a Only small hospitals versus medium or large and only Northeast region hospitals versus the Midwest were statistically significant (*).
study could also skew the results as it is known that angle fractures are treated with ORIF and are associated with the highest surgical complication rates.37 The primary strength of this study is the large and diverse sample representative of multiple institutions nationwide throughout the course of 1 year. Our study is the first
to correlate variables with increased hospital costs and LOS at a national level using a national sample database, thus enabling a more accurate assessment of mandible treatment costs in the United States and allowing a comparison of costs throughout the different regions and hospital types. Previous studies utilizing the NIS database limited their
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studies to only analyzing the primary ICD-9 code as the patients’ diagnosis, thus ignoring concurrent diagnoses and comorbid conditions. Our study analyzed all 10 listed diagnoses and assessed the associated cost and LOS for multiple different comorbidities.
Conclusion With an average hospitalization cost of $35,804 per person, the reduction of mandible fractures consumes extensive hospital resources. Uninsured African American males of low socioeconomic status comprise a disproportionately high percentage of mandible fracture patients treated nationally. Clinicians should consider HIV screening in patients with isolated mandible fractures given the greater than 3-fold increased likelihood of having HIV in these patients compared to the general population. Health care expenditures associated with the treatment of mandible fractures are higher for patients over age 40 and those with a history of mental illness, substance abuse, and CV disease. To improve outcomes and reduce hospital charges related to mandible fractures, outpatient resources and inpatient protocols should be implemented to address these factors. Author Contributions Israel Pena Jr., data collection and analysis, interpretation of data for the work, drafting and revision of content, substantial contributions to the design of the work; Laura Evelyn Roberts, data collection and analysis, interpretation of data for the work, drafting and revision of content, substantial contributions to the design of the work; W. Marshall Guy, analysis and interpretation of data for the work, drafting and revision of content; Jose P. Zevallos, analysis and interpretation of data for the work, substantial contributions to the design of the work, revision and approval of work.
Disclosures Competing interests: None. Sponsorships: None. Funding source: None.
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procedures. Research and Perspectives on Healthcare. 2007: 85:1-9. Ayanian J, Weissman J. Teaching hospitals and quality of care: a review of the literature. Milbank Q. 2002:80:569-593. Center for Disease Control and Prevention. www.cdc.gov. Accessed March 2014. National Institute of Mental Health. www.nimh.nih.gov. Accessed March 2014. National Health and Nutrition Examination Survey. www.heart .org. Accessed March 2014. Ellis E, Moos KF, El-Atar A, Arbor A. Ten years of mandibular fractures: an analysis of 2,137 cases. Oral Surg Oral Med Oral Pathol. 1985;59:120-129. Olson R, Fonseca R, Zeitler D, Osbon D. Fractures of the mandible: a review of 580 cases. J Maxillofac Surg. 1982:40: 23-28. Sojat A, Meisami T, Sandor G, Clokie C. The epidemiology of mandibular fractures treated at the toronto general hospital: a review of 246 cases. J Can Dent Assoc. 2001:67:640-644. Gutta R, Tracy K, Johnson C, James LE, Krishnan DG, Marciani RD. Outcomes of mandible fracture treatment at an academic tertiary hospital: a 5 year analysis. J Oral Maxillofac Surg. 2014:72:550-558. Fridrich KL, Pena-Velasco G, Olson RAJ. Changing trends with mandibular fractures: a review of 1067 cases. J Oral Maxillofac Surg. 1985;59:120. Bailey BJ, Newlands SD, Johnson JT. Head and Neck SurgeryOtolaryngology. Philadelphia, PA: Lippincott Williams & Wilkins; 2006.
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The Cost and Inpatient Burden of Treating Mandible Fractures: A Nationwide Inpatient Sample Database Analysis
Otolaryngology– Head and Neck Surgery 2014, Vol. 151(4) 591–598 Ó American Academy of Otolaryngology—Head and Neck Surgery Foundation 2014 Reprints and permission: sagepub.com/journalsPermissions.nav DOI: 10.1177/0194599814542590 http://otojournal.org
Israel Pena Jr, MD1, Laura Evelyn Roberts1, W. Marshall Guy, MD1, and Jose P. Zevallos, MD1
No sponsorships or competing interests have been disclosed for this article.
Abstract Objective. To discuss patient demographics, hospitalization characteristics, and costs associated with the treatment of mandible fractures.
reconstruction, open reduction internal fixation, length of stay, hospital cost Received February 1, 2014; revised April 11, 2014; accepted June 17, 2014.
Introduction
Study Design. Cross-sectional study. Setting. The 2009 Nationwide Inpatient Sample (NIS) database. Subjects/Methods. Patient demographics, hospital characteristics, fracture locations, and common comorbidities for patients with isolated mandible fractures were analyzed, and variables associated with increased cost and length of hospitalization stay were ascertained. Results. A total of 1481 patients were identified with isolated mandible fractures. The average age was 32, 85.4% were male, 39% were Caucasian, and 25% African American. Forty percent were from the lowest median household income quartile, and 77% were uninsured or government funded. The average length of stay (LOS) was 2.65 days, and average hospitalization cost was $35,804. A statistically significant increased LOS was associated with alcohol abuse, drug abuse, mental illness, diabetes mellitus type 2, cardiovascular disease, HIV, and age over 40. There was a statistically significant increased total cost associated with drug abuse, alcohol abuse, mental illness, cardiovascular disease, and age over 40. Conclusion. The average cost for treatment of mandible fractures was $35,804 per person with increased expenditures for older patients and those with a history of mental illness, cardiovascular disease, or substance abuse. To improve outcomes and reduce hospital charges, outpatient resources and inpatient protocols should be implemented to address the factors we identified as contributing to higher costs and increased hospital stay. Keywords isolated mandible fracture, facial fractures, jaw fracture, national inpatient sample database, facial plastic and
National Healthcare Expenditures Accounts data from 2011 show that the United States spends $2.7 trillion per year on health care, $8,680 per person, and is projected to continue to increase.1 In an effort to make health care delivery more efficient while maintaining high-quality care, it is important to investigate factors contributing to this nationwide problem. Nahlliah et al2 investigated patient characteristics and hospitalization charges associated with the management of all facial fractures on a national level using the 2008 Nationwide Inpatient Sample (NIS) database and found that facial fracture reduction in the United States contributed to an inpatient hospital cost of $1.06 billion. Mandible fractures are the most common facial fractures requiring reduction and account for more than half of all hospitalization charges and length of stay (LOS).2 Mandible fractures occur most commonly in adult males2-6 with a disproportionally high percentage (19.8%) of African Americans.2 Mandible fractures are most commonly due to assault, followed by motor vehicle accidents and accidental falls,2-4,7-11 with alcohol and drug abuse commonly reported comorbidities.2,12,13 Previous studies have evaluated the cost of treating mandible fractures among different settings. Outpatient 1 The Bobby R. Alford Department of Otolaryngology–Head and Neck Surgery, Baylor College of Medicine, Houston, Texas, USA
This article was presented as a poster at the 2013 AAO-HNSF Annual Meeting & OTO EXPO; September 29–October 3, 2013; Vancouver, British Columbia, Canada. Corresponding Author: Israel Pena Jr, MD, The Bobby R. Alford Department of Otolaryngology– Head and Neck Surgery, Baylor College of Medicine, One Baylor Plaza, NA102, Houston, Texas 77030, USA. Email: [email protected]
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repair of mandible fractures was shown to be more costefficient compared to repair after direct hospitalization,14,15 but a delay in treatment, after 72 hours, is also associated with an increase in infection rates for both closed reduction (CR) and open reduction and internal fixation (ORIF).16-19 According to Maloney et al,18 patients treated within 72 hours of presentation had a 0.6% infection rate compared to the average infection rate of 4.4% for mandible repairs. Despite this finding, Dillion et al2 showed that hospital admission resulted in a mean bill $5876 higher than that of patients who were not admitted, especially if transferred from an outside facility as opposed to being admitted from the emergency department. Mandible fractures are most commonly managed by ORIF due to more predictable healing and more precise reduction when significant displacement, malocclusion, or other midface fractures are present.20,21 ORIF is also associated with better functional results, decreased pain,22 quicker return to school or work,23 and decreased masticatory disability resulting from prolonged immobilization.24 Although ORIF is associated with initial increased cost2,7,20,25-29 and increased LOS7,25,27,28 compared to CR, the benefits of ORIF are of particular importance in the large population of noncompliant patients in which there is a greater risk for postoperative complications and a higher potential for long-term cost.27 Dodson et al26 found that postoperative infection contributed to an average additional cost of $11,637 per patient. To date, there have been no studies that have evaluated variables associated with discrepancies in cost and LOS in the treatment of mandible fractures on a national level. The purpose of this cross-sectional analysis was to identify the patient demographics and hospital characteristics associated with the treatment of mandible fractures and to correlate these factors with cost and LOS using a national hospital database. By identifying populations most at risk and comorbidities associated with higher costs, we hope to elucidate preventive interventions targeting these different groups and subsequently help to ameliorate the financial burden of mandible fractures on the health care system.
Materials and Methods Study Design/Sample
intubation, and patients with concurrent neurological injury including altered mental status, comatose, and intracranial bleed. The intention was to exclude those patients with complex injuries whose hospital course was not solely related to the treatment of their mandible fracture.
Variables The first variables examined were age, gender, race, income level, and insurance type. These characteristics were decided on to better understand the demographics of the patients requiring treatment for a mandible fracture. Age was further broken down into 2 brackets, age .40 and age \40, and average cost and LOS was determined for each bracket to extrapolate if a certain age group incurs greater costs. Income level was also further subdivided into categories including less than $39,000, $39,000 to 48,000, $48,000 to 63,000, and greater than $63,000. These variables were analyzed to determine the most common gender, race, average age, and income bracket level associated with mandible fractures as well as the average cost and LOS for each. Similarly, payment type was divided into Medicare, Medicaid, HMO/private, self-pay, other, and no charge. These data were analyzed to determine average cost and LOS depending on payer type. Other variables analyzed included hospital characteristics: bed size of hospital stratified into large hospitals (.100 beds), medium size hospitals (50-99 beds), and small hospitals (\ 50 beds); hospital location (urban vs rural); hospital region; and academic versus nonacademic hospital. These hospital characteristics were further analyzed to determine average cost and LOS. The comorbidities substance abuse, mental disorders, alcohol abuse, diabetes mellitus type 2 (DM2), cardiovascular (CV) disease, hepatitis C, and human immunodeficiency virus (HIV) were assessed in diagnosis fields 1 through 10 using ICD-9 codes. The average LOS and cost for cases with these prominent comorbidities were then determined and compared to overall average hospital LOS and cost. Information pertaining to location and number of fractures, type of surgical procedure (ORIF or CR), day hospitalization procedure was performed, and postoperative complications were also analyzed in terms of cost and LOS.
Data Analyses
A cross-sectional analysis was conducted by analyzing the 2009 Nationwide Inpatient Sample database for patients with isolated mandible fractures. Since it is a secondary data set made available through the AHRQ, Institutional Review Board approval was not required. The NIS data set provides hospital characteristics and information on nearly 100 patient- and hospital-related variables. Patients included in this study had an ICD-9 code (International Classification of Diseases, 9th Revision, Clinical Modification) for mandible fracture (802.20 through 802.37) listed as the primary admitting diagnosis. Exclusion criteria included patients with poly-trauma, defined as any additional fracture occurring outside the mandible, patients with severe respiratory distress requiring
Average cost and LOS were calculated from the information provided in the data set for each of the variables analyzed. These values were then compared using 2-tailed t tests, and a P value was calculated to determine statistical significance of the means. When more than 2 variables were compared, P values were based on all pairwise multiple comparison procedures (Dunn’s Method). A P value of \.05 was considered significant. All statistical analyses were performed using SigmaPlot v.12.5 (Systat, Inc, Chicago, Illinois) statistical software.
Results A total of 1481 patients with isolated mandible fractures were identified. Average age was 32 years, and the vast
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Table 1. Patient Demographic Statistics (N = 1481). Study Variable Age (yrs) \40 40 Gender Male Female Unknown Race White Black Hispanic Native American Asian Other Income \$39,000 $39,000-49,000 $48,000-63,000 .$63,000 Insurance type Medicare Medicaid Private Self-pay Other No charge
Table 2. Patient Comorbidities Statistics. Data (%) 32 1101 (74.3) 380 (25.7) 1265 (85.4) 204 (13.8) 12 (0.8) 573 367 176 7 13 108
(38.7) (24.8) (11.9) (0.5) (0.9) (7.3)
542 362 260 180
(40.3) (26.9) (19.3) (13.4)
91 362 334 454 192 48
(6.1) (24.4) (22.6) (30.7) (13) (3.2)
Study Variable Psychiatric disorder Present Not present Alcohol abuse Present Not present Drug abuse Present Not present DM 2 Present Not present CV disease Present Not present HIV Present Not present Hepatitis C Present Not present
Data (%)
81 (5.5) 1400 (94.5) 174 (11.7) 1307 (88.3) 95 (6.4) 1386 (93.6) 35 (2.4) 1446 (97.6) 160 (10.8) 1321 (89.2) 21 (1.4) 1460 (98.6) 27 (1.8) 1454 (98.2)
Abbreviations: DM2, diabetes mellitus type 2; CV, cardiovascular disease; HIV, human immunodeficiency virus.
Table 3. Hospital Demographic Statistics. Study Variable
majority of patients were male (85.4%). Thirty-nine percent of patients were Caucasian, 25% African American, 12% Hispanic, 7% other, and 1% Asian (Table 1). Twelve percent of patients had a history of alcohol abuse at presentation, and 10.7% had a history of illicit drug abuse. A history of mental illness was found in 5.5% of patients. Two percent of patients were diabetic, 1.4% had HIV, 1.8% had hepatitis C, and 10.8% had comorbid cardiovascular (CV) disease (Table 2). Forty percent of patients were from the lowest median household income quartile (earning less than $39,000), 27% from the second quartile ($39,000-$48,000), 19% third quartile ($48,000-$63,000), and 13% in the top household income quartile (.$63,000). Seventy-seven percent of patients were either uninsured or government funded (Table 1). Eighty-two percent of patients were treated in academic and 18% in nonacademic hospitals. Seventy-two percent of patients were treated at large hospitals (.100 beds), 24% in medium size hospitals (50-99 beds), and 4% in small hospitals (\50 beds). The majority of patients (95%) were treated in an urban hospital setting, and 66% were treated in the South or Northeast (Table 3). A minority of patients had a single fracture (41%). Angle fractures were the most common (42%), followed by symphysis (39%), body (34%),
Affiliation Academic Nonacademic Size Small Medium Large Location Rural Urban Region Northeast Midwest South West
Data (%)
1211 (82) 270 (18) 61 (4) 335 (23) 1037 (72) 80 (5) 1401 (95) 437 267 537 240
(30) (18) (36) (16)
condyle (24%), and ramus (9%). There was no statistical difference between location of fracture and cost or LOS. Ninety-six percent of patients underwent ORIF, 2% underwent CR, and the remaining 2% underwent surgical procedure not otherwise specified (NOS) with no associated increase in LOS or cost. Thirty-eight percent of patients
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underwent surgical intervention within 24 hours of admission, 83% underwent intervention within 72 hours, and there was a 0.5% complication rate, which included postoperative infection and hematoma, with no associated increase in LOS or cost. Mean LOS was 2.96 days for the entire cohort, and the average cost of hospitalization was $35,804 (Table 4). LOS was noted to be significantly higher in patients with a history of alcohol abuse (3.8 vs 2.85 days, P \ .001), drug abuse (4.68 vs 2.84 days, P \ .001), mental illness (3.98 vs 2.90 days, P = .005), DM2 (4.23 vs 2.93 days, P = .008), CV disease (3.93 vs 2.84, P \ .001), HIV (4.71 vs 2.93, P \ .001), and age over 40 (3.68 vs 2.71 days, P \ .001) (Tables 4, 5). Patients treated in academic institutions had a shorter LOS compared to those treated in nonacademic institutions (2.91 vs 3.17 days, P = .03), however this was not clinically significant (Table 6). No significant difference in average LOS was noted with income quartile, gender, race, comorbid hepatitis C, hospital region or size, or rural versus urban setting (Tables 4, 6). Total cost was significantly higher in patients with a history of drug abuse ($56,251 vs $34,399, P \ .001), alcohol abuse ($44,007 vs $34,656, P \ .001), psychiatric disorders ($37,422 vs $35,713, P = .047), as well as in patients older than 40 ($38,769 vs $34,782, P = .013) and in patients with CV disease ($43,554 vs $34,870, P \ .05). Though the Asian population had a high average cost ($47,692) and LOS (6.38 days), this was skewed by 1 outlier with a cost of $134,000 and LOS of 33 days due to anoxic brain injury and grand mal seizures. Regardless, this was not statistically significant. There was also no significant difference in total cost in terms of academic versus nonacademic hospitals, rural versus urban setting, race, gender, diabetes, HIV or hepatitis C status, income quartile, or insurance status (Tables 4-6).
Discussion The NIS database provides a 20% stratified sample of US hospital admissions, making it an ideal database to study isolated mandible fractures. In an effort to decrease the nationwide financial burden, our aim was to identify variables associated with increased cost of hospitalization and LOS for the treatment of isolated mandible fractures. With a sample population of 1481 patients that met our inclusion and exclusion criteria, our results confirm that isolated mandible fractures incur a significant financial burden with an average hospitalization cost per patient of $35,804. As supported by previous studies,2,7 we found that the majority of patients affected by isolated mandible fractures requiring treatment are uninsured (47%) males of lower socioeconomic status with a disproportionately high percentage of African Americans. Thirty-nine percent of the sample population was Caucasian and 25% African American (Table 1), which differs markedly from the national population of 77.9% Caucasians and 13.1% African Americans.30 Of the various patient demographics we studied, only age older than 40 was associated with a statistically significant increase in cost and LOS (Table 4).
In terms of hospital characteristics, our study found that smaller hospitals were associated with a significantly lower cost than medium and large hospitals, with no difference in the LOS between the 3. This may be related to the higher charges seen in larger cosmopolitan areas as well as academic institutions where larger hospitals are more likely to be located compared to rural settings. Interestingly, the only significant difference in terms of hospital location was the higher average charges seen in the Northeast versus the Midwest region even though the average LOS remained same in both areas. In order to reign in the excess costs in the Northeast, further studies would be needed to determine the etiology of the increased costs, which may be a reflection of higher costs of living, regional differences in malpractice risks and claims, or may reflect differences in inpatient care that could potentially be avoided. In comparing academic versus nonacademic institutions, academic institutions had an increased cost of hospitalization (P = .649) but a slightly more rapid patient turnover that was statistically significant yet clinically irrelevant (2.91 vs 3.17, P = .031) (Table 6). Many studies have reported similar findings with academic institutions accruing higher costs than nonacademic, which was partly attributed to the higher degree of severity of patients treated at academic institutions.31,32 In addition, Ayanian et al33 determined that academic hospitals had surgical times on average 36 minutes longer than nonacademic hospitals, thus acquiring higher surgical costs. Comorbidities were also analyzed (Tables 3, 5). Previous studies agree that alcohol and drug users have an increased incidence of facial fractures.2,7 While the national average of illicit alcohol/drug abuse is 9.1%, we reported an incidence of 12% alcohol abuse and 11% drug abuse.34 Alcoholics stayed approximately 1 day longer (P \ .001) and were billed almost $10,000 more compared to nonalcoholics (P \ .001). Numerous variables, including cost of treating intoxication/withdrawal states, prolonged wound healing with increased risk of infection, and unreliable compliance to follow-up may help to explain these data. Similar to the data on alcohol abuse, those with concurrent drug use stayed almost 2 days longer (P \ .001) and had an average cost of about $22,000 more (P \ .001). It is therefore essential to proactively recognize these patient populations quickly to address their disposition and postoperative care in order to minimize prolonged hospitalizations. In addition, implementing population-wide screening and intervention programs for substance abuse may potentially decrease the cost and LOS in these patients who present with isolated mandible fractures. Mental illnesses had a prevalence of 5.5%, notably higher than the overall national prevalence of 4.1%.35 Patients with psychiatric disorders stayed in the hospital 1 day longer (P = .005) with a hospital cost of almost $2000 more (P \ .047). CV disease was prevalent in 10.8% of patients (consistent with the national prevalence for our sample’s average age) and was associated with a hospitalization of over 1 day longer (P \ .001) and $9000 more
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Table 4. Mean Cost and LOS for Patient Demographic Variables. Study Variable Patient sample Age \40 40 Gender Male Female Race White Black Hispanic Native American Asian Income \$39,000 $39,000-48,000 $48,000-63,000 .$63,000 Insurance Medicare Medicaid Private Self-pay No charge
Mean Cost
P Value
Mean LOS
P Value
$35,804 — $34,782 $38,769 — $36,003 $34,760 — $34,576 $36,990 $38,248 $37,323 $47,692 — $33,864 $36,169 $35,314 $37,443 — $40,165 $37,601 $36,241 $36,414 $26,922
— .013*
2.65 — 2.71 3.68 — 2.96 2.96 — 2.97 2.58 2.99 3 6.38 — 2.8 3.09 2.89 3.38 — 3.41 2.82 3.12 2.87 2.27
— \.001
.479
.314
.368
.096
.618
.102
.312
.131
Abbreviations: LOS, length of stay. *Statistical significance.
(P \ .05) than those without CV disease.36 In addition, the grossly underreported prevalence of HIV in our patient population was 1.4%, markedly higher than the national prevalence, 0.38%, which includes both those diagnosed and those infected but undiagnosed.34 Clinicians should consider HIV screening in patients with isolated mandible fractures given the greater than threefold increased likelihood of having HIV in these patients compared to the general population due to the high morbidity and mortality associated with untreated HIV. Of note, patients with HIV or DM2 were hospitalized 1 day longer but accrued no significant difference in cost. It is unclear, however, from the NIS database whether the increased cost or LOS associated with these comorbidities was due to the management of these diseases or the disease impact on the treatment of mandible fractures. Therefore, further studies are indicated to differentiate these factors in order to understand how to eliminate the higher costs and/or LOS in these population subtypes. One of the major limitations of this study is the inability to analyze the itemized billing costs, but rather only the average cost of hospitalization per patient. We are therefore unable to establish a direct causal relationship between the variables assessed and the cost and LOS. The associations highlighted, though, can help to elucidate factors to be
aware of when treating patients with mandible fractures. Also, from the information provided by the NIS database, mode of injury could not be ascertained. Motor vehicle accidents and sports-related injuries are more likely to result in poly-trauma, and assault is most likely to result in an isolated mandible trauma.37,38 By intentionally excluding poly-trauma to analyze costs associated specifically with mandible fractures, our study was skewed to include a higher proportions of assault-associated injuries. Another weakness encountered is that the NIS database grossly underestimates the complication rates (0.5%) of treating isolated mandible fractures compared to other studies (5.3%) because it relies on ICD-9 diagnosis codes.39 It was unclear whether diagnoses such as malocclusion, nonunion, nerve injury, and broken tooth were secondary to the initial insult or were surgical complications, and they were therefore excluded as complications. There is much discrepancy in the literature regarding the most common mandible fracture location. The body, angle, and condyle are the top 3 most commonly cited locations.25,40,41 Our study found angle, symphysis, and body to be the most common locations. The underrepresentation of condylar fractures and exclusion of children in our study may be responsible for the low number of CR procedures (2%).42 The higher percentage of angle fractures in our
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Table 5. Mean Cost and LOS for Patient Comorbidities Variables. Study Variable Psychiatric disorder Present Not present Alcohol abuse Present Not present Drug abuse Present Not present DM2 Present Not present CV disease Present Not present HIV Present Not present Hepatitis C Present Not present
Mean Cost
$37,422 $35,713 — $44,007 $34,656 — $56,251 $34,399 — $39,697 $35,711 — $43,554 $34,870 — $36,388 $35,797 — $42,028 $35,690
P Value
Mean LOS
\.047*
— 3.98 2.90 — 3.80 2.85 — 4.68 2.84 — 4.23 2.93 — 3.93 2.84 — 4.71 2.93 — 3.52 2.95
\.001*
\.001*
.106
\.050*
.317
.283
P Value .005*
\.001*
\.001*
.008*
\.001*
\.001*
.367
Abbreviations: LOS, length of stay; DM2, diabetes mellitus type 2; CV, cardiovascular disease; HIV, human immunodeficiency virus. *Statistical significance.
Table 6. Mean Cost and LOS for Hospital Characteristics.a Study Variable Affiliation Academic Nonacademic Size Small Medium Large Location Rural Urban Region Northeast Midwest South West
Mean Cost
P Value
Mean LOS
P Value
— $36,185 $34,087 — $26,225 $34,914 $36,996 — $29,257 $36,181 — $40,238 $30,242 $34,523 $36,786
.649
— 2.91 3.17 — 2.43 2.82 3.04 — 2.78 2.97 — 2.94 2.94 2.92 3.10
.031*
.005*
.22
.005*
.602
.542
.963
Abbreviation: LOS, length of stay. a Only small hospitals versus medium or large and only Northeast region hospitals versus the Midwest were statistically significant (*).
study could also skew the results as it is known that angle fractures are treated with ORIF and are associated with the highest surgical complication rates.37 The primary strength of this study is the large and diverse sample representative of multiple institutions nationwide throughout the course of 1 year. Our study is the first
to correlate variables with increased hospital costs and LOS at a national level using a national sample database, thus enabling a more accurate assessment of mandible treatment costs in the United States and allowing a comparison of costs throughout the different regions and hospital types. Previous studies utilizing the NIS database limited their
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studies to only analyzing the primary ICD-9 code as the patients’ diagnosis, thus ignoring concurrent diagnoses and comorbid conditions. Our study analyzed all 10 listed diagnoses and assessed the associated cost and LOS for multiple different comorbidities.
Conclusion With an average hospitalization cost of $35,804 per person, the reduction of mandible fractures consumes extensive hospital resources. Uninsured African American males of low socioeconomic status comprise a disproportionately high percentage of mandible fracture patients treated nationally. Clinicians should consider HIV screening in patients with isolated mandible fractures given the greater than 3-fold increased likelihood of having HIV in these patients compared to the general population. Health care expenditures associated with the treatment of mandible fractures are higher for patients over age 40 and those with a history of mental illness, substance abuse, and CV disease. To improve outcomes and reduce hospital charges related to mandible fractures, outpatient resources and inpatient protocols should be implemented to address these factors. Author Contributions Israel Pena Jr., data collection and analysis, interpretation of data for the work, drafting and revision of content, substantial contributions to the design of the work; Laura Evelyn Roberts, data collection and analysis, interpretation of data for the work, drafting and revision of content, substantial contributions to the design of the work; W. Marshall Guy, analysis and interpretation of data for the work, drafting and revision of content; Jose P. Zevallos, analysis and interpretation of data for the work, substantial contributions to the design of the work, revision and approval of work.
Disclosures Competing interests: None. Sponsorships: None. Funding source: None.
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